from sklearn_benchmarks.report import Reporting
import pandas as pd
pd.set_option('display.max_colwidth', None)
pd.set_option('display.max_columns', None)
pd.set_option('display.max_rows', None)
scikit-learn vs. scikit-learn-intelex (Intel® oneAPI) benchmarks: perfect hyperparameters match¶Reporting(config="config.yml").run()
KNeighborsClassifier: scikit-learn (1.0.dev0) vs. scikit-learn-intelex (2021.20210705.191215)¶All estimators share the following hyperparameters: algorithm=brute.
| estimator | function | n_samples_train | n_samples | n_features | n_iter | mean_sklearn | stdev_sklearn | throughput | latency | n_jobs | n_neighbors | accuracy_score_sklearn | accuracy_score_sklearnex | mean_sklearnex | stdev_sklearnex | speedup | stdev_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KNeighborsClassifier | fit | 1000000 | 1000000 | 100 | NaN | 0.135 | 0.0 | 5.922 | 0.0 | 1 | 100 | NaN | NaN | 0.486 | 0.0 | 0.278 | 0.0 | See | See |
| 3 | KNeighborsClassifier | fit | 1000000 | 1000000 | 100 | NaN | 0.128 | 0.0 | 6.259 | 0.0 | -1 | 100 | NaN | NaN | 0.470 | 0.0 | 0.272 | 0.0 | See | See |
| 6 | KNeighborsClassifier | fit | 1000000 | 1000000 | 100 | NaN | 0.130 | 0.0 | 6.149 | 0.0 | -1 | 1 | NaN | NaN | 0.470 | 0.0 | 0.277 | 0.0 | See | See |
| 9 | KNeighborsClassifier | fit | 1000000 | 1000000 | 100 | NaN | 0.126 | 0.0 | 6.350 | 0.0 | 1 | 5 | NaN | NaN | 0.471 | 0.0 | 0.267 | 0.0 | See | See |
| 12 | KNeighborsClassifier | fit | 1000000 | 1000000 | 100 | NaN | 0.124 | 0.0 | 6.435 | 0.0 | 1 | 1 | NaN | NaN | 0.470 | 0.0 | 0.264 | 0.0 | See | See |
| 15 | KNeighborsClassifier | fit | 1000000 | 1000000 | 100 | NaN | 0.124 | 0.0 | 6.462 | 0.0 | -1 | 5 | NaN | NaN | 0.472 | 0.0 | 0.262 | 0.0 | See | See |
| 18 | KNeighborsClassifier | fit | 1000000 | 1000000 | 2 | NaN | 0.054 | 0.0 | 0.296 | 0.0 | 1 | 100 | NaN | NaN | 0.100 | 0.0 | 0.541 | 0.0 | See | See |
| 21 | KNeighborsClassifier | fit | 1000000 | 1000000 | 2 | NaN | 0.058 | 0.0 | 0.278 | 0.0 | -1 | 100 | NaN | NaN | 0.098 | 0.0 | 0.589 | 0.0 | See | See |
| 24 | KNeighborsClassifier | fit | 1000000 | 1000000 | 2 | NaN | 0.055 | 0.0 | 0.291 | 0.0 | -1 | 1 | NaN | NaN | 0.098 | 0.0 | 0.562 | 0.0 | See | See |
| 27 | KNeighborsClassifier | fit | 1000000 | 1000000 | 2 | NaN | 0.073 | 0.0 | 0.220 | 0.0 | 1 | 5 | NaN | NaN | 0.098 | 0.0 | 0.740 | 0.0 | See | See |
| 30 | KNeighborsClassifier | fit | 1000000 | 1000000 | 2 | NaN | 0.055 | 0.0 | 0.293 | 0.0 | 1 | 1 | NaN | NaN | 0.102 | 0.0 | 0.537 | 0.0 | See | See |
| 33 | KNeighborsClassifier | fit | 1000000 | 1000000 | 2 | NaN | 0.054 | 0.0 | 0.295 | 0.0 | -1 | 5 | NaN | NaN | 0.098 | 0.0 | 0.552 | 0.0 | See | See |
| estimator | function | n_samples_train | n_samples | n_features | n_iter | mean_sklearn | stdev_sklearn | throughput | latency | n_jobs | n_neighbors | accuracy_score_sklearn | accuracy_score_sklearnex | mean_sklearnex | stdev_sklearnex | speedup | stdev_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KNeighborsClassifier | predict | 1000000 | 1000 | 100 | NaN | 21.523 | 0.054 | 0.0 | 0.022 | 1 | 100 | 0.943 | 0.684 | 1.738 | 0.005 | 12.382 | 0.048 | See | See |
| 2 | KNeighborsClassifier | predict | 1000000 | 1 | 100 | NaN | 0.209 | 0.002 | 0.0 | 0.209 | 1 | 100 | 1.000 | 0.000 | 0.087 | 0.000 | 2.410 | 0.024 | See | See |
| 4 | KNeighborsClassifier | predict | 1000000 | 1000 | 100 | NaN | 35.152 | 0.000 | 0.0 | 0.035 | -1 | 100 | 0.943 | 0.927 | 1.783 | 0.006 | 19.713 | 0.061 | See | See |
| 5 | KNeighborsClassifier | predict | 1000000 | 1 | 100 | NaN | 0.191 | 0.015 | 0.0 | 0.191 | -1 | 100 | 1.000 | 1.000 | 0.087 | 0.000 | 2.194 | 0.167 | See | See |
| 7 | KNeighborsClassifier | predict | 1000000 | 1000 | 100 | NaN | 26.514 | 0.109 | 0.0 | 0.027 | -1 | 1 | 0.703 | 0.792 | 1.737 | 0.004 | 15.267 | 0.072 | See | See |
| 8 | KNeighborsClassifier | predict | 1000000 | 1 | 100 | NaN | 0.181 | 0.015 | 0.0 | 0.181 | -1 | 1 | 0.000 | 1.000 | 0.088 | 0.002 | 2.066 | 0.180 | See | See |
| 10 | KNeighborsClassifier | predict | 1000000 | 1000 | 100 | NaN | 21.631 | 0.036 | 0.0 | 0.022 | 1 | 5 | 0.807 | 0.792 | 1.737 | 0.004 | 12.453 | 0.034 | See | See |
| 11 | KNeighborsClassifier | predict | 1000000 | 1 | 100 | NaN | 0.206 | 0.001 | 0.0 | 0.206 | 1 | 5 | 1.000 | 1.000 | 0.087 | 0.001 | 2.363 | 0.016 | See | See |
| 13 | KNeighborsClassifier | predict | 1000000 | 1000 | 100 | NaN | 12.811 | 0.220 | 0.0 | 0.013 | 1 | 1 | 0.703 | 0.684 | 1.738 | 0.004 | 7.372 | 0.128 | See | See |
| 14 | KNeighborsClassifier | predict | 1000000 | 1 | 100 | NaN | 0.196 | 0.000 | 0.0 | 0.196 | 1 | 1 | 0.000 | 0.000 | 0.088 | 0.000 | 2.235 | 0.011 | See | See |
| 16 | KNeighborsClassifier | predict | 1000000 | 1000 | 100 | NaN | 35.288 | 0.000 | 0.0 | 0.035 | -1 | 5 | 0.807 | 0.927 | 1.784 | 0.004 | 19.782 | 0.047 | See | See |
| 17 | KNeighborsClassifier | predict | 1000000 | 1 | 100 | NaN | 0.202 | 0.014 | 0.0 | 0.202 | -1 | 5 | 1.000 | 1.000 | 0.088 | 0.001 | 2.300 | 0.162 | See | See |
| 19 | KNeighborsClassifier | predict | 1000000 | 1000 | 2 | NaN | 20.001 | 0.048 | 0.0 | 0.020 | 1 | 100 | 0.987 | 0.973 | 0.251 | 0.000 | 79.740 | 0.228 | See | See |
| 20 | KNeighborsClassifier | predict | 1000000 | 1 | 2 | NaN | 0.027 | 0.001 | 0.0 | 0.027 | 1 | 100 | 1.000 | 1.000 | 0.005 | 0.000 | 5.487 | 0.470 | See | See |
| 22 | KNeighborsClassifier | predict | 1000000 | 1000 | 2 | NaN | 33.915 | 0.000 | 0.0 | 0.034 | -1 | 100 | 0.987 | 0.985 | 0.298 | 0.000 | 113.619 | 0.167 | See | See |
| 23 | KNeighborsClassifier | predict | 1000000 | 1 | 2 | NaN | 0.035 | 0.002 | 0.0 | 0.035 | -1 | 100 | 1.000 | 1.000 | 0.005 | 0.000 | 6.954 | 0.800 | See | See |
| 25 | KNeighborsClassifier | predict | 1000000 | 1000 | 2 | NaN | 24.380 | 0.124 | 0.0 | 0.024 | -1 | 1 | 0.978 | 0.983 | 0.253 | 0.001 | 96.522 | 0.570 | See | See |
| 26 | KNeighborsClassifier | predict | 1000000 | 1 | 2 | NaN | 0.022 | 0.002 | 0.0 | 0.022 | -1 | 1 | 1.000 | 1.000 | 0.005 | 0.000 | 4.304 | 0.555 | See | See |
| 28 | KNeighborsClassifier | predict | 1000000 | 1000 | 2 | NaN | 20.129 | 0.025 | 0.0 | 0.020 | 1 | 5 | 0.983 | 0.983 | 0.253 | 0.001 | 79.423 | 0.200 | See | See |
| 29 | KNeighborsClassifier | predict | 1000000 | 1 | 2 | NaN | 0.028 | 0.000 | 0.0 | 0.028 | 1 | 5 | 1.000 | 1.000 | 0.005 | 0.000 | 5.173 | 0.409 | See | See |
| 31 | KNeighborsClassifier | predict | 1000000 | 1000 | 2 | NaN | 10.190 | 0.018 | 0.0 | 0.010 | 1 | 1 | 0.978 | 0.973 | 0.251 | 0.000 | 40.616 | 0.087 | See | See |
| 32 | KNeighborsClassifier | predict | 1000000 | 1 | 2 | NaN | 0.015 | 0.000 | 0.0 | 0.015 | 1 | 1 | 1.000 | 1.000 | 0.005 | 0.000 | 2.998 | 0.258 | See | See |
| 34 | KNeighborsClassifier | predict | 1000000 | 1000 | 2 | NaN | 34.033 | 0.000 | 0.0 | 0.034 | -1 | 5 | 0.983 | 0.985 | 0.299 | 0.001 | 113.804 | 0.271 | See | See |
| 35 | KNeighborsClassifier | predict | 1000000 | 1 | 2 | NaN | 0.035 | 0.002 | 0.0 | 0.035 | -1 | 5 | 1.000 | 1.000 | 0.005 | 0.000 | 6.712 | 0.774 | See | See |
KNeighborsClassifier_kd_tree: scikit-learn (1.0.dev0) vs. scikit-learn-intelex (2021.20210705.191215)¶All estimators share the following hyperparameters: algorithm=kd_tree.
| estimator | function | n_samples_train | n_samples | n_features | n_iter | mean_sklearn | stdev_sklearn | throughput | latency | n_jobs | n_neighbors | accuracy_score_sklearn | accuracy_score_sklearnex | mean_sklearnex | stdev_sklearnex | speedup | stdev_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | NaN | 2.809 | 0.0 | 0.028 | 0.0 | -1 | 5 | NaN | NaN | 0.729 | 0.0 | 3.855 | 0.0 | See | See |
| 3 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | NaN | 2.819 | 0.0 | 0.028 | 0.0 | 1 | 1 | NaN | NaN | 0.722 | 0.0 | 3.903 | 0.0 | See | See |
| 6 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | NaN | 2.825 | 0.0 | 0.028 | 0.0 | 1 | 5 | NaN | NaN | 0.727 | 0.0 | 3.888 | 0.0 | See | See |
| 9 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | NaN | 2.832 | 0.0 | 0.028 | 0.0 | -1 | 100 | NaN | NaN | 0.730 | 0.0 | 3.879 | 0.0 | See | See |
| 12 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | NaN | 2.794 | 0.0 | 0.029 | 0.0 | 1 | 100 | NaN | NaN | 0.731 | 0.0 | 3.824 | 0.0 | See | See |
| 15 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | NaN | 2.803 | 0.0 | 0.029 | 0.0 | -1 | 1 | NaN | NaN | 0.729 | 0.0 | 3.846 | 0.0 | See | See |
| 18 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 2 | NaN | 0.730 | 0.0 | 0.022 | 0.0 | -1 | 5 | NaN | NaN | 0.487 | 0.0 | 1.498 | 0.0 | See | See |
| 21 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 2 | NaN | 0.727 | 0.0 | 0.022 | 0.0 | 1 | 1 | NaN | NaN | 0.476 | 0.0 | 1.528 | 0.0 | See | See |
| 24 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 2 | NaN | 0.724 | 0.0 | 0.022 | 0.0 | 1 | 5 | NaN | NaN | 0.441 | 0.0 | 1.643 | 0.0 | See | See |
| 27 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 2 | NaN | 0.728 | 0.0 | 0.022 | 0.0 | -1 | 100 | NaN | NaN | 0.435 | 0.0 | 1.675 | 0.0 | See | See |
| 30 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 2 | NaN | 0.723 | 0.0 | 0.022 | 0.0 | 1 | 100 | NaN | NaN | 0.493 | 0.0 | 1.467 | 0.0 | See | See |
| 33 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 2 | NaN | 0.729 | 0.0 | 0.022 | 0.0 | -1 | 1 | NaN | NaN | 0.463 | 0.0 | 1.575 | 0.0 | See | See |
| estimator | function | n_samples_train | n_samples | n_features | n_iter | mean_sklearn | stdev_sklearn | throughput | latency | n_jobs | n_neighbors | accuracy_score_sklearn | accuracy_score_sklearnex | mean_sklearnex | stdev_sklearnex | speedup | stdev_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | NaN | 0.851 | 0.006 | 0.000 | 0.001 | -1 | 5 | 0.977 | 0.962 | 0.200 | 0.002 | 4.256 | 0.044 | See | See |
| 2 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | NaN | 0.003 | 0.000 | 0.000 | 0.003 | -1 | 5 | 1.000 | 1.000 | 0.000 | 0.000 | 6.109 | 3.180 | See | See |
| 4 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | NaN | 0.739 | 0.005 | 0.000 | 0.001 | 1 | 1 | 0.966 | 0.964 | 0.603 | 0.005 | 1.225 | 0.013 | See | See |
| 5 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | NaN | 0.001 | 0.000 | 0.000 | 0.001 | 1 | 1 | 1.000 | 1.000 | 0.001 | 0.000 | 0.813 | 0.430 | See | See |
| 7 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | NaN | 1.436 | 0.008 | 0.000 | 0.001 | 1 | 5 | 0.977 | 0.954 | 0.111 | 0.003 | 12.939 | 0.325 | See | See |
| 8 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | NaN | 0.001 | 0.000 | 0.000 | 0.001 | 1 | 5 | 1.000 | 1.000 | 0.000 | 0.000 | 3.657 | 2.099 | See | See |
| 10 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | NaN | 2.832 | 0.030 | 0.000 | 0.003 | -1 | 100 | 0.972 | 0.962 | 0.209 | 0.005 | 13.533 | 0.383 | See | See |
| 11 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | NaN | 0.004 | 0.001 | 0.000 | 0.004 | -1 | 100 | 1.000 | 1.000 | 0.000 | 0.000 | 9.764 | 5.354 | See | See |
| 13 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | NaN | 4.873 | 0.037 | 0.000 | 0.005 | 1 | 100 | 0.972 | 0.954 | 0.109 | 0.002 | 44.878 | 0.932 | See | See |
| 14 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | NaN | 0.002 | 0.001 | 0.000 | 0.002 | 1 | 100 | 1.000 | 1.000 | 0.000 | 0.000 | 8.524 | 5.306 | See | See |
| 16 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | NaN | 0.440 | 0.004 | 0.000 | 0.000 | -1 | 1 | 0.966 | 0.964 | 0.604 | 0.007 | 0.728 | 0.011 | See | See |
| 17 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | NaN | 0.003 | 0.000 | 0.000 | 0.003 | -1 | 1 | 1.000 | 1.000 | 0.001 | 0.000 | 2.555 | 1.246 | See | See |
| 19 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 2 | NaN | 0.023 | 0.001 | 0.001 | 0.000 | -1 | 5 | 0.982 | 0.981 | 0.001 | 0.000 | 20.882 | 5.852 | See | See |
| 20 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 2 | NaN | 0.002 | 0.000 | 0.000 | 0.002 | -1 | 5 | 1.000 | 1.000 | 0.000 | 0.000 | 20.613 | 17.626 | See | See |
| 22 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 2 | NaN | 0.020 | 0.001 | 0.001 | 0.000 | 1 | 1 | 0.974 | 0.983 | 0.006 | 0.001 | 3.217 | 0.401 | See | See |
| 23 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 2 | NaN | 0.001 | 0.000 | 0.000 | 0.001 | 1 | 1 | 1.000 | 1.000 | 0.000 | 0.000 | 4.964 | 4.377 | See | See |
| 25 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 2 | NaN | 0.021 | 0.001 | 0.001 | 0.000 | 1 | 5 | 0.982 | 0.972 | 0.001 | 0.000 | 27.907 | 11.048 | See | See |
| 26 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 2 | NaN | 0.001 | 0.000 | 0.000 | 0.001 | 1 | 5 | 1.000 | 1.000 | 0.000 | 0.000 | 5.746 | 4.832 | See | See |
| 28 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 2 | NaN | 0.040 | 0.002 | 0.000 | 0.000 | -1 | 100 | 0.984 | 0.981 | 0.001 | 0.000 | 36.624 | 10.196 | See | See |
| 29 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 2 | NaN | 0.002 | 0.000 | 0.000 | 0.002 | -1 | 100 | 1.000 | 1.000 | 0.000 | 0.000 | 20.823 | 17.587 | See | See |
| 31 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 2 | NaN | 0.045 | 0.003 | 0.000 | 0.000 | 1 | 100 | 0.984 | 0.972 | 0.001 | 0.000 | 62.903 | 22.168 | See | See |
| 32 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 2 | NaN | 0.001 | 0.000 | 0.000 | 0.001 | 1 | 100 | 1.000 | 1.000 | 0.000 | 0.000 | 5.684 | 4.774 | See | See |
| 34 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 2 | NaN | 0.021 | 0.001 | 0.001 | 0.000 | -1 | 1 | 0.974 | 0.983 | 0.006 | 0.001 | 3.394 | 0.479 | See | See |
| 35 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 2 | NaN | 0.002 | 0.000 | 0.000 | 0.002 | -1 | 1 | 1.000 | 1.000 | 0.000 | 0.000 | 17.999 | 14.323 | See | See |
KMeans_tall: scikit-learn (1.0.dev0) vs. scikit-learn-intelex (2021.20210705.191215)¶All estimators share the following hyperparameters: algorithm=full, n_clusters=3, max_iter=30, n_init=1, tol=1e-16.
| estimator | function | n_samples_train | n_samples | n_features | n_iter_sklearn | mean_sklearn | stdev_sklearn | throughput | latency | init | adjusted_rand_score_sklearn | n_iter_sklearnex | adjusted_rand_score_sklearnex | mean_sklearnex | stdev_sklearnex | speedup | stdev_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KMeans_tall | fit | 1000000 | 1000000 | 2 | 30 | 0.556 | 0.0 | 0.863 | 0.0 | random | NaN | 30 | NaN | 0.382 | 0.0 | 1.456 | 0.0 | See | See |
| 3 | KMeans_tall | fit | 1000000 | 1000000 | 2 | 30 | 0.561 | 0.0 | 0.856 | 0.0 | k-means++ | NaN | 30 | NaN | 0.408 | 0.0 | 1.373 | 0.0 | See | See |
| 6 | KMeans_tall | fit | 1000000 | 1000000 | 100 | 30 | 6.301 | 0.0 | 3.809 | 0.0 | random | NaN | 30 | NaN | 2.611 | 0.0 | 2.413 | 0.0 | See | See |
| 9 | KMeans_tall | fit | 1000000 | 1000000 | 100 | 30 | 6.186 | 0.0 | 3.880 | 0.0 | k-means++ | NaN | 30 | NaN | 2.769 | 0.0 | 2.234 | 0.0 | See | See |
| estimator | function | n_samples_train | n_samples | n_features | n_iter_sklearn | mean_sklearn | stdev_sklearn | throughput | latency | init | adjusted_rand_score_sklearn | n_iter_sklearnex | adjusted_rand_score_sklearnex | mean_sklearnex | stdev_sklearnex | speedup | stdev_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KMeans_tall | predict | 1000000 | 1000 | 2 | 30 | 0.001 | 0.0 | 0.360 | 0.000 | random | 0.001 | 30 | 0.001 | 0.0 | 0.0 | 9.662 | 6.921 | See | See |
| 2 | KMeans_tall | predict | 1000000 | 1 | 2 | 30 | 0.001 | 0.0 | 0.000 | 0.001 | random | 1.000 | 30 | 1.000 | 0.0 | 0.0 | 10.607 | 8.210 | See | See |
| 4 | KMeans_tall | predict | 1000000 | 1000 | 2 | 30 | 0.001 | 0.0 | 0.363 | 0.000 | k-means++ | 0.001 | 30 | 0.001 | 0.0 | 0.0 | 9.179 | 6.192 | See | See |
| 5 | KMeans_tall | predict | 1000000 | 1 | 2 | 30 | 0.001 | 0.0 | 0.000 | 0.001 | k-means++ | 1.000 | 30 | 1.000 | 0.0 | 0.0 | 10.868 | 7.533 | See | See |
| 7 | KMeans_tall | predict | 1000000 | 1000 | 100 | 30 | 0.002 | 0.0 | 14.949 | 0.000 | random | 0.002 | 30 | 0.002 | 0.0 | 0.0 | 6.190 | 3.222 | See | See |
| 8 | KMeans_tall | predict | 1000000 | 1 | 100 | 30 | 0.001 | 0.0 | 0.019 | 0.001 | random | 1.000 | 30 | 1.000 | 0.0 | 0.0 | 10.064 | 7.081 | See | See |
| 10 | KMeans_tall | predict | 1000000 | 1000 | 100 | 30 | 0.002 | 0.0 | 15.562 | 0.000 | k-means++ | 0.002 | 30 | 0.002 | 0.0 | 0.0 | 5.875 | 2.812 | See | See |
| 11 | KMeans_tall | predict | 1000000 | 1 | 100 | 30 | 0.001 | 0.0 | 0.019 | 0.001 | k-means++ | 1.000 | 30 | 1.000 | 0.0 | 0.0 | 10.052 | 6.738 | See | See |
KMeans_short: scikit-learn (1.0.dev0) vs. scikit-learn-intelex (2021.20210705.191215)¶All estimators share the following hyperparameters: algorithm=full, n_clusters=300, max_iter=20, n_init=1, tol=1e-16.
| estimator | function | n_samples_train | n_samples | n_features | n_iter_sklearn | mean_sklearn | stdev_sklearn | throughput | latency | init | adjusted_rand_score_sklearn | n_iter_sklearnex | adjusted_rand_score_sklearnex | mean_sklearnex | stdev_sklearnex | speedup | stdev_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KMeans_short | fit | 10000 | 10000 | 2 | 20 | 0.073 | 0.0 | 0.044 | 0.0 | random | NaN | 20 | NaN | 0.081 | 0.0 | 0.900 | 0.0 | See | See |
| 3 | KMeans_short | fit | 10000 | 10000 | 2 | 20 | 0.204 | 0.0 | 0.016 | 0.0 | k-means++ | NaN | 20 | NaN | 0.026 | 0.0 | 7.694 | 0.0 | See | See |
| 6 | KMeans_short | fit | 10000 | 10000 | 100 | 20 | 0.186 | 0.0 | 0.860 | 0.0 | random | NaN | 20 | NaN | 0.286 | 0.0 | 0.650 | 0.0 | See | See |
| 9 | KMeans_short | fit | 10000 | 10000 | 100 | 20 | 0.555 | 0.0 | 0.289 | 0.0 | k-means++ | NaN | 20 | NaN | 0.104 | 0.0 | 5.319 | 0.0 | See | See |
| estimator | function | n_samples_train | n_samples | n_features | n_iter_sklearn | mean_sklearn | stdev_sklearn | throughput | latency | init | adjusted_rand_score_sklearn | n_iter_sklearnex | adjusted_rand_score_sklearnex | mean_sklearnex | stdev_sklearnex | speedup | stdev_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KMeans_short | predict | 10000 | 1000 | 2 | 20 | 0.002 | 0.0 | 0.186 | 0.000 | random | 0.000 | 20 | 0.001 | 0.001 | 0.0 | 3.371 | 0.826 | See | See |
| 2 | KMeans_short | predict | 10000 | 1 | 2 | 20 | 0.001 | 0.0 | 0.000 | 0.001 | random | 1.000 | 20 | 1.000 | 0.000 | 0.0 | 10.074 | 6.663 | See | See |
| 4 | KMeans_short | predict | 10000 | 1000 | 2 | 20 | 0.002 | 0.0 | 0.189 | 0.000 | k-means++ | 0.000 | 20 | 0.003 | 0.000 | 0.0 | 3.482 | 0.723 | See | See |
| 5 | KMeans_short | predict | 10000 | 1 | 2 | 20 | 0.001 | 0.0 | 0.000 | 0.001 | k-means++ | 1.000 | 20 | 1.000 | 0.000 | 0.0 | 10.018 | 6.551 | See | See |
| 7 | KMeans_short | predict | 10000 | 1000 | 100 | 20 | 0.002 | 0.0 | 6.858 | 0.000 | random | 0.255 | 20 | 0.259 | 0.001 | 0.0 | 2.319 | 0.393 | See | See |
| 8 | KMeans_short | predict | 10000 | 1 | 100 | 20 | 0.001 | 0.0 | 0.012 | 0.001 | random | 1.000 | 20 | 1.000 | 0.000 | 0.0 | 8.759 | 5.501 | See | See |
| 10 | KMeans_short | predict | 10000 | 1000 | 100 | 20 | 0.002 | 0.0 | 6.726 | 0.000 | k-means++ | 0.238 | 20 | 0.360 | 0.001 | 0.0 | 2.407 | 0.420 | See | See |
| 11 | KMeans_short | predict | 10000 | 1 | 100 | 20 | 0.001 | 0.0 | 0.012 | 0.001 | k-means++ | 1.000 | 20 | 1.000 | 0.000 | 0.0 | 8.700 | 5.154 | See | See |
LogisticRegression: scikit-learn (1.0.dev0) vs. scikit-learn-intelex (2021.20210705.191215)¶All estimators share the following hyperparameters: penalty=l2, dual=False, tol=0.0001, C=1.0, fit_intercept=True, intercept_scaling=1, class_weight=nan, random_state=nan, solver=lbfgs, max_iter=100, multi_class=auto, verbose=0, warm_start=False, n_jobs=nan, l1_ratio=nan.
| estimator | function | n_samples_train | n_samples | n_features | n_iter | mean_sklearn | stdev_sklearn | throughput | latency | class_weight | l1_ratio | n_jobs | random_state | accuracy_score | mean_sklearnex | stdev_sklearnex | speedup | stdev_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | LogisticRegression | fit | 1000000 | 1000000 | 100 | [20] | 11.724 | 0.0 | [-0.10063635] | 0.000 | NaN | NaN | NaN | NaN | NaN | 1.974 | 0.0 | 5.939 | 0.0 | See | See |
| 3 | LogisticRegression | fit | 1000 | 1000 | 10000 | [26] | 0.836 | 0.0 | [2.48752162] | 0.001 | NaN | NaN | NaN | NaN | NaN | 0.850 | 0.0 | 0.984 | 0.0 | See | See |
| estimator | function | n_samples_train | n_samples | n_features | n_iter | mean_sklearn | stdev_sklearn | throughput | latency | class_weight | l1_ratio | n_jobs | random_state | accuracy_score | mean_sklearnex | stdev_sklearnex | speedup | stdev_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | LogisticRegression | predict | 1000000 | 1000 | 100 | [20] | 0.000 | 0.0 | [56.37524774] | 0.0 | NaN | NaN | NaN | NaN | 0.541 | 0.000 | 0.0 | 0.849 | 0.458 | See | See |
| 2 | LogisticRegression | predict | 1000000 | 1 | 100 | [20] | 0.000 | 0.0 | [0.26083909] | 0.0 | NaN | NaN | NaN | NaN | 0.000 | 0.000 | 0.0 | 0.366 | 0.404 | See | See |
| 4 | LogisticRegression | predict | 1000 | 100 | 10000 | [26] | 0.002 | 0.0 | [136.14673581] | 0.0 | NaN | NaN | NaN | NaN | 0.240 | 0.003 | 0.0 | 0.549 | 0.117 | See | See |
| 5 | LogisticRegression | predict | 1000 | 1 | 10000 | [26] | 0.000 | 0.0 | [23.41266627] | 0.0 | NaN | NaN | NaN | NaN | 0.000 | 0.001 | 0.0 | 0.135 | 0.116 | See | See |
Ridge: scikit-learn (1.0.dev0) vs. scikit-learn-intelex (2021.20210705.191215)¶All estimators share the following hyperparameters: alpha=1.0, fit_intercept=True, normalize=deprecated, copy_X=True, max_iter=nan, tol=0.001, solver=auto, random_state=nan.
| estimator | function | n_samples_train | n_samples | n_features | n_iter | mean_sklearn | stdev_sklearn | throughput | latency | max_iter | random_state | r2_score | mean_sklearnex | stdev_sklearnex | speedup | stdev_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | Ridge | fit | 1000 | 1000 | 10000 | NaN | 0.173 | 0.0 | 0.461 | 0.0 | NaN | NaN | NaN | 0.175 | 0.0 | 0.989 | 0.0 | See | See |
| 3 | Ridge | fit | 1000000 | 1000000 | 100 | NaN | 1.443 | 0.0 | 0.554 | 0.0 | NaN | NaN | NaN | 0.230 | 0.0 | 6.264 | 0.0 | See | See |
| estimator | function | n_samples_train | n_samples | n_features | n_iter | mean_sklearn | stdev_sklearn | throughput | latency | max_iter | random_state | r2_score | mean_sklearnex | stdev_sklearnex | speedup | stdev_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | Ridge | predict | 1000 | 1000 | 10000 | NaN | 0.011 | 0.000 | 7.082 | 0.0 | NaN | NaN | 0.106 | 0.018 | 0.0 | 0.622 | 0.017 | See | See |
| 2 | Ridge | predict | 1000 | 1 | 10000 | NaN | 0.000 | 0.000 | 1.074 | 0.0 | NaN | NaN | NaN | 0.000 | 0.0 | 0.727 | 0.740 | See | See |
| 4 | Ridge | predict | 1000000 | 1000 | 100 | NaN | 0.000 | 0.001 | 1.973 | 0.0 | NaN | NaN | 1.000 | 0.000 | 0.0 | 1.846 | 3.792 | See | See |
| 5 | Ridge | predict | 1000000 | 1 | 100 | NaN | 0.000 | 0.000 | 0.014 | 0.0 | NaN | NaN | NaN | 0.000 | 0.0 | 0.628 | 0.741 | See | See |